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Confirmed on the employer's own hiring board on Nov 5, 2026. First seen by Alion on Oct 21, 2026. Google scores B on the Alion truth index.

Overview
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Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

About the job

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

As a Cloud Platform and Infrastructure Engineer, you will provide exceptional technical guidance to customers adopting Google Cloud Platform (GCP) services. This includes providing best practices on secure foundational cloud implementations, automated provisioning of infrastructure and applications, cloud-ready application architectures, and more. You will also provide prescriptive guidance in ensuring that customers receive the best of what GCP can offer and have the best experience in migrating, building, modernizing, and maintaining applications in GCP. Additionally, you will work closely with Product Management and Product Engineering to drive excellence in Google Cloud products and features.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

Poland: zł188000 - zł192000 (PLN) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Provide domain expertise in cloud platforms and infrastructure; solving complex cloud platform challenges.
  • Work with customers to design and implement Cloud based technical architectures, migration approaches, and application optimizations that enable business objectives.
  • Be a technical advisor and perform troubleshooting to resolve technical challenges for customers.
  • Create and deliver best practice recommendations, tutorials, blog articles, and sample code.
  • Travel up to 30% for in-region for meetings, technical reviews, and onsite delivery activities.

Qualifications

Minimum qualifications:

  • Bachelor’s degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
  • Experience in writing and reading/debugging code written in a general purpose coding language (e.g., Java, C, C++, Python, Shell, Go or JavaScript, etc.) and in virtualization and orchestration frameworks.
  • Experience as a system administrator with Linux/Unix systems and debugging issues across the hardware/software boundary on enterprise-grade server infrastructure.
  • Experience troubleshooting and advocating for customer needs, and triaging technical issues across the stack (e.g., hardware faults, low-level software, networking, virtualization, kernel drivers, firmware, performance).

Preferred qualifications:

  • Experience working with distributed systems, and familiarity with common solutions, design patterns, or best practices.
  • Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
  • Familiarity with containerization and orchestration technologies like Kubernetes or Slurm in an on-prem or cloud environment.
  • Experience with ML frameworks (e.g., TensorFlow, PyTorch), and understanding of the AI/ML training and inference lifecycle.
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